Literature DB >> 28964116

Revealing kinetics and state-dependent binding properties of IKur-targeting drugs that maximize atrial fibrillation selectivity.

Nicholas Ellinwood1, Dobromir Dobrev2, Stefano Morotti1, Eleonora Grandi1.   

Abstract

The KV1.5 potassium channel, which underlies the ultra-rapid delayed-rectifier current (IKur) and is predominantly expressed in atria vs. ventricles, has emerged as a promising target to treat atrial fibrillation (AF). However, while numerous KV1.5-selective compounds have been screened, characterized, and tested in various animal models of AF, evidence of antiarrhythmic efficacy in humans is still lacking. Moreover, current guidelines for pre-clinical assessment of candidate drugs heavily rely on steady-state concentration-response curves or IC50 values, which can overlook adverse cardiotoxic effects. We sought to investigate the effects of kinetics and state-dependent binding of IKur-targeting drugs on atrial electrophysiology in silico and reveal the ideal properties of IKur blockers that maximize anti-AF efficacy and minimize pro-arrhythmic risk. To this aim, we developed a new Markov model of IKur that describes KV1.5 gating based on experimental voltage-clamp data in atrial myocytes from patient right-atrial samples in normal sinus rhythm. We extended the IKur formulation to account for state-specificity and kinetics of KV1.5-drug interactions and incorporated it into our human atrial cell model. We simulated 1- and 3-Hz pacing protocols in drug-free conditions and with a [drug] equal to the IC50 value. The effects of binding and unbinding kinetics were determined by examining permutations of the forward (kon) and reverse (koff) binding rates to the closed, open, and inactivated states of the KV1.5 channel. We identified a subset of ideal drugs exhibiting anti-AF electrophysiological parameter changes at fast pacing rates (effective refractory period prolongation), while having little effect on normal sinus rhythm (limited action potential prolongation). Our results highlight that accurately accounting for channel interactions with drugs, including kinetics and state-dependent binding, is critical for developing safer and more effective pharmacological anti-AF options.

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Year:  2017        PMID: 28964116      PMCID: PMC5573366          DOI: 10.1063/1.5000226

Source DB:  PubMed          Journal:  Chaos        ISSN: 1054-1500            Impact factor:   3.642


  54 in total

1.  In silico study on the effects of IKur block kinetics on prolongation of human action potential after atrial fibrillation-induced electrical remodeling.

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2.  Modifying L-type calcium current kinetics: consequences for cardiac excitation and arrhythmia dynamics.

Authors:  Aman Mahajan; Daisuke Sato; Yohannes Shiferaw; Ali Baher; Lai-Hua Xie; Robert Peralta; Riccardo Olcese; Alan Garfinkel; Zhilin Qu; James N Weiss
Journal:  Biophys J       Date:  2008-01-15       Impact factor: 4.033

3.  Binding site of a novel Kv1.5 blocker: a "foot in the door" against atrial fibrillation.

Authors:  Niels Decher; Pradeep Kumar; Teresa Gonzalez; Bernard Pirard; Michael C Sanguinetti
Journal:  Mol Pharmacol       Date:  2006-07-11       Impact factor: 4.436

4.  Regulation of the transient outward K(+) current by Ca(2+)/calmodulin-dependent protein kinases II in human atrial myocytes.

Authors:  S Tessier; P Karczewski; E G Krause; Y Pansard; C Acar; M Lang-Lazdunski; J J Mercadier; S N Hatem
Journal:  Circ Res       Date:  1999-10-29       Impact factor: 17.367

5.  Human atrial action potential and Ca2+ model: sinus rhythm and chronic atrial fibrillation.

Authors:  Eleonora Grandi; Sandeep V Pandit; Niels Voigt; Antony J Workman; Dobromir Dobrev; José Jalife; Donald M Bers
Journal:  Circ Res       Date:  2011-09-15       Impact factor: 17.367

6.  The ultrarapid and the transient outward K(+) current in human atrial fibrillation. Their possible role in postoperative atrial fibrillation.

Authors:  M C Brandt; L Priebe; T Böhle; M Südkamp; D J Beuckelmann
Journal:  J Mol Cell Cardiol       Date:  2000-10       Impact factor: 5.000

7.  Improved Prediction of Drug-Induced Torsades de Pointes Through Simulations of Dynamics and Machine Learning Algorithms.

Authors:  M Cummins Lancaster; E A Sobie
Journal:  Clin Pharmacol Ther       Date:  2016-05-20       Impact factor: 6.875

Review 8.  Atrial selectivity of antiarrhythmic drugs.

Authors:  Ursula Ravens; Claire Poulet; Erich Wettwer; Michael Knaut
Journal:  J Physiol       Date:  2013-06-03       Impact factor: 5.182

9.  Risperidone reduces K+ currents in human atrial myocytes and prolongs repolarization in human myocardium.

Authors:  Pascale Gluais; Michèle Bastide; Daniel Grandmougin; Georges Fayad; Monique Adamantidis
Journal:  Eur J Pharmacol       Date:  2004-08-23       Impact factor: 4.432

10.  Cellular basis for the negative dromotropic effect of adenosine on rabbit single atrioventricular nodal cells.

Authors:  D Wang; J C Shryock; L Belardinelli
Journal:  Circ Res       Date:  1996-04       Impact factor: 17.367

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  10 in total

Review 1.  Computational modeling: What does it tell us about atrial fibrillation therapy?

Authors:  Eleonora Grandi; Dobromir Dobrev; Jordi Heijman
Journal:  Int J Cardiol       Date:  2019-01-25       Impact factor: 4.164

2.  Populations of in silico myocytes and tissues reveal synergy of multiatrial-predominant K+ -current block in atrial fibrillation.

Authors:  Haibo Ni; Alex Fogli Iseppe; Wayne R Giles; Sanjiv M Narayan; Henggui Zhang; Andrew G Edwards; Stefano Morotti; Eleonora Grandi
Journal:  Br J Pharmacol       Date:  2020-08-09       Impact factor: 8.739

3.  Erratum: "Revealing kinetics and state-dependent binding properties of IKur-targeting drugs that maximize atrial fibrillation selectivity" [Chaos 27, 093918 (2017)].

Authors:  Nicholas Ellinwood; Dobromir Dobrev; Stefano Morotti; Eleonora Grandi
Journal:  Chaos       Date:  2017-10       Impact factor: 3.642

4.  In Silico Assessment of Efficacy and Safety of IKur Inhibitors in Chronic Atrial Fibrillation: Role of Kinetics and State-Dependence of Drug Binding.

Authors:  Nicholas Ellinwood; Dobromir Dobrev; Stefano Morotti; Eleonora Grandi
Journal:  Front Pharmacol       Date:  2017-11-07       Impact factor: 5.810

Review 5.  In Vitro and In Silico Risk Assessment in Acquired Long QT Syndrome: The Devil Is in the Details.

Authors:  William Lee; Monique J Windley; Jamie I Vandenberg; Adam P Hill
Journal:  Front Physiol       Date:  2017-11-16       Impact factor: 4.566

6.  When Does the IC50 Accurately Assess the Blocking Potency of a Drug?

Authors:  Julio Gomis-Tena; Brandon M Brown; Jordi Cano; Beatriz Trenor; Pei-Chi Yang; Javier Saiz; Colleen E Clancy; Lucia Romero
Journal:  J Chem Inf Model       Date:  2020-03-10       Impact factor: 4.956

Review 7.  Computational Modeling of Electrophysiology and Pharmacotherapy of Atrial Fibrillation: Recent Advances and Future Challenges.

Authors:  Márcia Vagos; Ilsbeth G M van Herck; Joakim Sundnes; Hermenegild J Arevalo; Andrew G Edwards; Jussi T Koivumäki
Journal:  Front Physiol       Date:  2018-09-04       Impact factor: 4.566

8.  Closed and open state dependent block of potassium channels cause opposing effects on excitability - a computational approach.

Authors:  Richard Ågren; Johanna Nilsson; Peter Århem
Journal:  Sci Rep       Date:  2019-06-03       Impact factor: 4.379

Review 9.  Understanding AF Mechanisms Through Computational Modelling and Simulations.

Authors:  Konstantinos N Aronis; Rheeda L Ali; Jialiu A Liang; Shijie Zhou; Natalia A Trayanova
Journal:  Arrhythm Electrophysiol Rev       Date:  2019-07

10.  Synergistic Anti-arrhythmic Effects in Human Atria with Combined Use of Sodium Blockers and Acacetin.

Authors:  Haibo Ni; Dominic G Whittaker; Wei Wang; Wayne R Giles; Sanjiv M Narayan; Henggui Zhang
Journal:  Front Physiol       Date:  2017-11-23       Impact factor: 4.566

  10 in total

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